174 resultados para Stochastic transport equation


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We describe a noniterative method for recovering optical absorption coefficient distribution from the absorbed energy map reconstructed using simulated and noisy boundary pressure measurements. The source reconstruction problem is first solved for the absorbed energy map corresponding to single- and multiple-source illuminations from the side of the imaging plane. It is shown that the absorbed energy map and the absorption coefficient distribution, recovered from the single-source illumination with a large variation in photon flux distribution, have signal-to-noise ratios comparable to those of the reconstructed parameters from a more uniform photon density distribution corresponding to multiple-source illuminations. The absorbed energy map is input as absorption coefficient times photon flux in the time-independent diffusion equation (DE) governing photon transport to recover the photon flux in a single step. The recovered photon flux is used to compute the optical absorption coefficient distribution from the absorbed energy map. In the absence of experimental data, we obtain the boundary measurements through Monte Carlo simulations, and we attempt to address the possible limitations of the DE model in the overall reconstruction procedure.

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Carbon nanofibers of 50–500 nm diameter and several micrometer length were synthesized by high-temperature pyrolysis of dihydro-2,5-furandione (C4H4O3) in the temperature range of 600–980 °C. The formation of both graphitic and non-graphitic structured carbon fibers was observed in high-resolution transmission electron microscope. The Raman spectra of the samples showed the presence of both the D and G bands of varying intensity and sharpness. The low-temperature electrical transport studies on the samples have shown interesting metal–insulator transitions. The films showed variable range hopping conduction in the insulating regime and power law behavior in the critical regime at low temperatures.

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A Trotter product formula is established for unitary quantum stochastic processes governed by quantum stochastic differential equations with constant bounded coefficients.

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Magmas, a conserved mammalian protein essential for eukaryotic development, is overexpressed in prostate carcinomas and cells exposed to granulocyte-macrophage colony-stimulating factor (GM-CSF). Reduced Magmas expression resulted in decreased proliferative rates in cultured cells. However, the cellular function of Magmas is still elusive. In this report, we have showed that human Magmas is an ortholog of Saccharomyces cerevisiae Pam16 having similar functions and is critical for protein translocation across mitochondrial inner membrane. Human Magmas shows a complete growth complementation of delta pam16 yeast cells at all temperatures. On the basis of our analysis, we report that Magmas localizes into mitochondria and is peripherally associated with inner mitochondrial membrane in yeast and humans. Magmas forms a stable subcomplex with J-protein Pam18 or DnaJC19 through its C-terminal region and is tethered to TIM23 complex of yeast and humans. Importantly, amino acid alterations in Magmas leads to reduced stability of the subcomplex with Pam18 that results in temperature sensitivity and in vivo protein translocation defects in yeast cells. These observations highlight the central role of Magmas in protein import and mitochondria biogenesis. In humans, absence of a functional DnaJC19 leads to dilated cardiac myophathic syndrome (DCM), a genetic disorder with characteristic features of cardiac myophathy and neurodegeneration. We propose that the mutations resulting in decreased stability of functional Magmas:DnaJC19 subcomplex at human TIM23 channel leads to impaired protein import and cellular respiration in DCM patients. Together, we propose a model showing how Magmas:DnaJC19 subcomplex is associated with TIM23 complex and thus regulates mitochondrial import process.

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La0.5Li0.5TiO3 perovskite was synthesized by various wet chemical methods. By adopting low temperature methods of preparation lithium loss from the material is prevented. La0.5Li0.5TiO3 (LLTO) was formed with cubic symmetry at 1473 K. LLTO was formed at relatively lower temperature by using hydrothermal preparation method. PVA gel-decomposition route yield tetragonal LLTO on annealing the dried gel at 1473 K. By using gel-carbonate route LiTi2O4 minor phase was found to remain even after heat-treatment at 1473 K. The hydroxylation of LLTO was done in deionized water as well as in dilute acetic acid medium. By hydroxylation process incorporation of hydroxyls and leaching out of Li+ was observed from the material. The Li+ concentration of these compositions was examined by AAS. The electrical conductivities of these compositions were measured by dc and ac impedance techniques at elevated temperatures. The activation energies of electrical conduction for these compositions were estimated from the experimental results. The measured activation energy of Li+ conduction is 0.34 eV. Unhydroxylated samples exhibit only Li+ conduction, whereas, the hydroxylated LLTO show proton conductivity at 298-550 K in addition to Li+ conductivity. The effect of Zr or Ce substitution in place of Ti were attempted. La0.5Li0.5ZrO3 Perovskite was not formed; instead pyrochlore phase (La2Zr2O7) along with monoclinic ZrO2 phases was observed above 1173 K; below 1173 K cubic ZrO2 is stable. (La0.5Li0.5)(2)CeO4 solid solution was formed in the case of Ce substitution at Ti sublattice on heat-treatment up to 1673 K. (c) 2005 Springer Science + Business Media, Inc.

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Gene expression noise results in protein number distributions ranging from long-tailed to Gaussian. We show how long-tailed distributions arise from a stochastic model of the constituent chemical reactions and suggest that, in conjunction with cooperative switches, they lead to more sensitive selection of a subpopulation of cells with high protein number than is possible with Gaussian distributions. Single-cell-tracking experiments are presented to validate some of the assumptions of the stochastic simulations. We also examine the effect of DNA looping on the shape of protein distributions. We further show that when switches are incorporated in the regulation of a gene via a feedback loop, the distributions can become bimodal. This might explain the bimodal distribution of certain morphogens during early embryogenesis.

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The problem of admission control of packets in communication networks is studied in the continuous time queueing framework under different classes of service and delayed information feedback. We develop and use a variant of a simulation based two timescale simultaneous perturbation stochastic approximation (SPSA) algorithm for finding an optimal feedback policy within the class of threshold type policies. Even though SPSA has originally been designed for continuous parameter optimization, its variant for the discrete parameter case is seen to work well. We give a proof of the hypothesis needed to show convergence of the algorithm on our setting along with a sketch of the convergence analysis. Extensive numerical experiments with the algorithm are illustrated for different parameter specifications. In particular, we study the effect of feedback delays on the system performance.

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The flow of a liquid on single-walled carbon nanotube bundles induces an electrical signal (voltage/current) in the sample along the direction of the flow. The electrical response is found to be logarithmic in the flow speed over a wide range. The magnitude of the flow induced electrical signal generated depends sensitively on the ionic conductivity and the polar nature of the liquid, and electrical biasing of the nanotubes can control its direction. Our measurements suggest that the dominant mechanism responsible for this highly sub-linear response should involve a direct forcing of the free charge carriers in the nanotubes by the fluctuating Coulombic field of the liquid flowing past it.

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The Hybrid approach introduced by the authors for at-site modeling of annual and periodic streamflows in earlier works is extended to simulate multi-site multi-season streamflows. It bears significance in integrated river basin planning studies. This hybrid model involves: (i) partial pre-whitening of standardized multi-season streamflows at each site using a parsimonious linear periodic model; (ii) contemporaneous resampling of the resulting residuals with an appropriate block size, using moving block bootstrap (non-parametric, NP) technique; and (iii) post-blackening the bootstrapped innovation series at each site, by adding the corresponding parametric model component for the site, to obtain generated streamflows at each of the sites. It gains significantly by effectively utilizing the merits of both parametric and NP models. It is able to reproduce various statistics, including the dependence relationships at both spatial and temporal levels without using any normalizing transformations and/or adjustment procedures. The potential of the hybrid model in reproducing a wide variety of statistics including the run characteristics, is demonstrated through an application for multi-site streamflow generation in the Upper Cauvery river basin, Southern India. (C) 2004 Elsevier B.V. All rights reserved.

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Ion transport in a recently demonstrated promising soft matter solid plastic-polymer electrolyte is discussed here in the context of solvent dynamics and ion association. The plastic-polymer composite electrolytes display liquid-like ionic conductivity in the solid state,compliable mechanical strength (similar to 1 MPa), and wide electrochemical voltage stability (>= 5 V). Polyacrylonitrile (PAN) dispersed in lithium perchlorate (LiClO4)-succinonitrile (SN) was chosen as the model system for the study (abbreviated LiClO4-SN:PAN). Systematic observation of various mid-infrared isomer and ion association bands as a function of temperature and polyme concentration shows an effective increase in trans conformer concentration along with free Li+ ion concentration. This strongly supports the view that enhancement in LiClO4-SN:PAN ionic conductivity over the neat plastic electrolyte (LiClO4-SN) is due to both increase in charge mobility and concentration. The ionic conductivity and infrared spectroscopy studies are supported by Brillouin light scattering. For the LiClO4-SN:PAN composites, a peak at 17 GHz was observed in addition to the normal trans-gauche isomerism (as in neat SN) at 12 GHz. The fast process is attributed to increased dynamics of those SN molecules whose energy barrier of transition from gauche to trans has reduced under influences induced by the changes in temperature and polymer concentration. The observations from ionic conductivity, spectroscopy, and light scattering studies were further supplemented by temperature dependent nuclear magnetic resonance H-1 and Li-7 line width measurements.

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Benedict-Webb-Rubin equation of state constants for NO, O2, and the equilibrium mixture N2O4 ⇄ 2NO2 are reported.

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The rate of absorption of amino acids from mixtures has been studied in the silkworm midgut by using an in vitro perfusion technique. The rates differ for individual amino acids. A characteristic absorption pattern is observed which is independent of the amino acid composition of the mixture used. The metabolic inhibitors dinitrophenol and cyanide have no effect on the amino acid transport from mixtures. Based on these results an energy-independent, carrier-mediated transport is postulated.

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We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time,recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through a pseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets of measurements involving various load cases, we expedite the speed of thePD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small.

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We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time, recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through apseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets ofmeasurements involving various load cases, we expedite the speed of the PD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small. Copyright (C) 2009 John Wiley & Sons, Ltd.

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The association parameter in the diffuswn equaiior, dye fo Wiike one Chong has been interpreted in deferminable properties, thus permitting easily the calculation of the same for unknown systems. The proposed eqyotion a!se holds goods for water as soiute in organic solvenfs. The over-all percentage error remains the sarrse as that of the original equation.